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Locate the example manuscript in the folder exercises/3_papaja_example_manuscript and open the file manuscript.pdf or manuscript.docx.
notefield and each author’s role field can simply be omitted.
title: "Distorted estimates of implicit and explicit learning in applications of the process-dissociation procedure to the SRT task"
shorttitle: "Distorted PD estimates in sequence learning"
author:
- name: "Christoph Stahl"
affiliation: ""
corresponding: yes
address: "Herbert-Lewin-Straße 2, 50931 Köln"
email: "christoph.stahl@uni-koeln.de"
- name: "Marius Barth"
affiliation: ""
- name: "Hilde Haider"
affiliation: ""
affiliation:
- id: ""
institution: "University of Cologne"
authornote: |
This work was funded by Deutsche Forschungsgemeinschaft grants STA-1269/1-1 and HA-5447/8-1.
abstract: |
We investigated potential biases affecting the validity of the process-dissociation (PD) procedure when applied to sequence learning.
Participants were or were not exposed to a serial reaction time task (SRTT) with two types of pseudo-random materials.
Afterwards, participants worked on a free or cued generation task under inclusion and exclusion instructions.
Results showed that pre-experimental response tendencies,
non-associative learning of location frequencies,
and the usage of cue locations introduced bias to PD estimates.
These biases may lead to erroneous conclusions regarding the presence of implicit and explicit knowledge.
Potential remedies for these problems are discussed.
keywords: "implicit learning, serial reaction time task, process-dissociation procedure, response bias"
wordcount: "8,167"
draft and linenumbers options in the YAML front matter.
draft: yes
linenumbers: no
"doc" class option.
classoption: "doc"
citr to insert citations.
Add the the bibliography files to the YAML front matter:
bibliography: ["references.bib", "r-references.bib"]
The following is an examplary excerpt of what you citations could look like:
One of the most frequently utilized paradigms in the field of implicit learning is the serial reaction time task (SRTT) originating from @nissen_attentional_1987. [...] Even with more sensitive tests including the recently introduced wagering task [@dienes_gambling_2010; @haider_old_2011; @persaud_postdecision_2007] or the process-dissociation procedure [@destrebecqz_can_2001; @haider_old_2011; @jacoby_process_1991], explicit knowledge of the sequence is rare.
Locate and open the R-script analyses.R and data folder data accompanying the example manuscript in the folder exercises/3_papaja_example_manuscript.
apa_print() to report the results of one or more analysis using in-line code chunks in your papaja document.
Use the section comments (e.g., ## ----setup----) to split the R script into meaningful code chunks and use the section headings as chunk names.
The following is a minimal example of how to report one hypothesis test of one of the analyses.
```{r setup}
# load packages
library("papaja")
library("afex")
```
```{r prepare-data}
acquisition <- readRDS("data/acquisition-task.rds")
```
```{r acquisition-rt}
# within the permuted-material group, high vs. low frequency locations can be distinguished
tmp.perm <- acquisition[
acquisition$error == 0 &
acquisition$trial > 1 &
acquisition$included_participant &
acquisition$material == "Permuted" &
!is.na(acquisition$frequency),
]
permuted_aov <- aov_ez(
data = tmp.perm
, dv = "SRI"
, within = c("block", "frequency")
, id = "id"
)
permuted_res <- apa_print(permuted_aov)```
The effect of *frequency* was significant, `r permuted_res$full_result$frequency`.
```{r acquisition-rt-plot}
apa_lineplot(
data = tmp.perm
, id = "id"
, dv = "SRI"
, factors = c("block", "frequency")
, dispersion = wsci
, ylab = ""
, args_lines = list(lty = c("solid", "solid"))
, args_points = list(pch = c(21, 21))
, args_legend = list(legend = c("High", "Low"), title = "Location frequency")
, ylim = c(475, 650)
, jit = .05
)
```
Locate the section proportion-correct-table-appendix at the end of the R-script analyses.R.
apa_table().
col_spanners and midrules to structure the table. To add a caption, use the argument caption. See ?apa_table.
```{r proportion-correct-table}
tmp <- generation[
generation$included_participant &
generation$repetition == 0 &
generation$post_repetition == 0,
]
# calculate proportion of regular transitions per participant
agg <- aggregate(
formula = correct_SOC ~ material + generation + order + PD_instruction + id
, data = tmp
, FUN = mean
, na.rm = TRUE
)
# calculate condition means and standard errors
means <- aggregate(
formula = cbind(M = correct_SOC) ~ material + generation + order + PD_instruction
, data = agg
, FUN = mean
)
SEs <- aggregate(
formula = cbind(`SE` = correct_SOC) ~ material + generation + order + PD_instruction
, data = agg
, FUN = se
)
# merge means and CI width
tab <- merge(means, SEs)
# bind Inclusion and Exclusion side-by-side
tab <- cbind(tab[tab$PD_instruction == "Inclusion", ], tab[tab$PD_instruction == "Exclusion", c("M", "SE")])
tab$PD_instruction <- NULL
tab$material <- gsub(tab$material, pattern = "-", replacement = " ", fixed = TRUE)
tab$generation <- as.character(tab$generation)
tab$generation[duplicated(paste0(tab$material, tab$generation))] <- ""
tab$material[duplicated(tab$material)] <- ""
apa_table(
tab
, row.names = FALSE
, col_spanners = list(Inclusion = c(4, 5), Exclusion = c(6, 7))
, midrules = c(4, 8, 12)
, caption = "Means (M) and standard errors (SE) of proportion of correctly generated second-order
conditionals (SOCs)."
, placement = NULL
)
```
Place the table in the appendix of your document. To start an appendix, use the following special heading:
# (APPENDIX) Appendix {-}
\newpage
# References
::: {#refs custom-style="Bibliography"}
:::
\newpage
# (APPENDIX) Appendix {-}
```{r proportion-correct-table-appendix}
apa_table(
tab
, row.names = FALSE
, col_spanners = list(Inclusion = c(4, 5), Exclusion = c(6, 7))
, midrules = c(4, 8, 12)
, caption = "Means (M) and standard errors (SE) of proportion of correctly generated second-order
conditionals (SOCs)."
, placement = NULL
)
```
(ref:reference-name).
(ref:table-caption) Means ($M$) and standard errors ($\mathit{SE}$) of proportion of correctly generated second-order conditionals (SOCs).```{r proportion-correct-table} apa_table( tab , row.names = FALSE , col_spanners = list(Inclusion = c(4, 5), Exclusion = c(6, 7)) , midrules = c(4, 8, 12), caption = "(ref:table-caption)", placement = NULL ) ```